Model Comparison

LongCat-Flash-Thinking vs Qwen3 VL 4B Instruct

LongCat-Flash-Thinking significantly outperforms across most benchmarks. Qwen3 VL 4B Instruct is 2.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

LongCat-Flash-Thinking outperforms in 4 benchmarks (AIME 2025, BFCL-v3, MMLU-Pro, MMLU-Redux), while Qwen3 VL 4B Instruct is better at 0 benchmarks.

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Tue Apr 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 4B Instruct costs less

For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 3.0x more expensive than Qwen3 VL 4B Instruct ($0.10/1M tokens).

For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 2.0x more expensive than Qwen3 VL 4B Instruct ($0.60/1M tokens).

In conclusion, LongCat-Flash-Thinking is more expensive than Qwen3 VL 4B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Apr 21 2026 • llm-stats.com
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Instruct
Input tokens$0.10
Output tokens$0.60
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

556.0B diff

LongCat-Flash-Thinking has 556.0B more parameters than Qwen3 VL 4B Instruct, making it 13900.0% larger.

Meituan
LongCat-Flash-Thinking
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Instruct
4.0Bparameters
560.0B
LongCat-Flash-Thinking
4.0B
Qwen3 VL 4B Instruct

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Instruct accepts 262,144 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. Qwen3 VL 4B Instruct can generate longer responses up to 262,144 tokens, while LongCat-Flash-Thinking is limited to 128,000 tokens.

Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Instruct
Input262,144 tokens
Output262,144 tokens
Tue Apr 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Instruct supports multimodal inputs, whereas LongCat-Flash-Thinking does not.

Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Thinking

Text
Images
Audio
Video

Qwen3 VL 4B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Thinking is licensed under MIT, while Qwen3 VL 4B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

LongCat-Flash-Thinking

MIT

Open weights

Qwen3 VL 4B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-09-22.

They likely represent similar generations of model development.

LongCat-Flash-Thinking

Sep 22, 2025

7 months ago

Qwen3 VL 4B Instruct

Sep 22, 2025

7 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

LongCat-Flash-Thinking is available from Meituan. Qwen3 VL 4B Instruct is available from DeepInfra.

LongCat-Flash-Thinking

meituan logo
Meituan
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen3 VL 4B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Meituan
Higher AIME 2025 score (90.6% vs 46.6%)
Higher BFCL-v3 score (74.4% vs 63.3%)
Higher MMLU-Pro score (82.6% vs 67.1%)
Higher MMLU-Redux score (89.3% vs 81.5%)
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Instruct

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Thinking
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Instruct

FAQ

Common questions about LongCat-Flash-Thinking vs Qwen3 VL 4B Instruct

LongCat-Flash-Thinking significantly outperforms across most benchmarks. LongCat-Flash-Thinking is made by Meituan and Qwen3 VL 4B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%. Qwen3 VL 4B Instruct scores DocVQAtest: 95.3%, ScreenSpot: 94.0%, OCRBench: 88.1%, MMBench-V1.1: 85.1%, AI2D: 84.1%.
Qwen3 VL 4B Instruct is 3.0x cheaper for input tokens. LongCat-Flash-Thinking costs $0.30/M input and $1.20/M output via meituan. Qwen3 VL 4B Instruct costs $0.10/M input and $0.60/M output via deepinfra.
LongCat-Flash-Thinking supports 128K tokens and Qwen3 VL 4B Instruct supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 262K), input pricing ($0.30 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Thinking is developed by Meituan and Qwen3 VL 4B Instruct is developed by Alibaba Cloud / Qwen Team.